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Empirical Bayes Analysis of Quantitative Proteomics Experiments

Author

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  • Adam A Margolin
  • Shao-En Ong
  • Monica Schenone
  • Robert Gould
  • Stuart L Schreiber
  • Steven A Carr
  • Todd R Golub

Abstract

Background: Advances in mass spectrometry-based proteomics have enabled the incorporation of proteomic data into systems approaches to biology. However, development of analytical methods has lagged behind. Here we describe an empirical Bayes framework for quantitative proteomics data analysis. The method provides a statistical description of each experiment, including the number of proteins that differ in abundance between 2 samples, the experiment's statistical power to detect them, and the false-positive probability of each protein. Methodology/Principal Findings: We analyzed 2 types of mass spectrometric experiments. First, we showed that the method identified the protein targets of small-molecules in affinity purification experiments with high precision. Second, we re-analyzed a mass spectrometric data set designed to identify proteins regulated by microRNAs. Our results were supported by sequence analysis of the 3′ UTR regions of predicted target genes, and we found that the previously reported conclusion that a large fraction of the proteome is regulated by microRNAs was not supported by our statistical analysis of the data. Conclusions/Significance: Our results highlight the importance of rigorous statistical analysis of proteomic data, and the method described here provides a statistical framework to robustly and reliably interpret such data.

Suggested Citation

  • Adam A Margolin & Shao-En Ong & Monica Schenone & Robert Gould & Stuart L Schreiber & Steven A Carr & Todd R Golub, 2009. "Empirical Bayes Analysis of Quantitative Proteomics Experiments," PLOS ONE, Public Library of Science, vol. 4(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0007454
    DOI: 10.1371/journal.pone.0007454
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    References listed on IDEAS

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    1. Daehyun Baek & Judit Villén & Chanseok Shin & Fernando D. Camargo & Steven P. Gygi & David P. Bartel, 2008. "The impact of microRNAs on protein output," Nature, Nature, vol. 455(7209), pages 64-71, September.
    2. Matthias Selbach & Björn Schwanhäusser & Nadine Thierfelder & Zhuo Fang & Raya Khanin & Nikolaus Rajewsky, 2008. "Widespread changes in protein synthesis induced by microRNAs," Nature, Nature, vol. 455(7209), pages 58-63, September.
    3. Lyris M. F. de Godoy & Jesper V. Olsen & Jürgen Cox & Michael L. Nielsen & Nina C. Hubner & Florian Fröhlich & Tobias C. Walther & Matthias Mann, 2008. "Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast," Nature, Nature, vol. 455(7217), pages 1251-1254, October.
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